Hamayesh Arwin Alborz همایش آروین البرز MHHJR MHHJR 2 3 2026 08 18 Wearable Biosensors and Artificial Intelligence for Personalized Health Monitoring Wearable Biosensors and Artificial Intelligence for Personalized Health Monitoring 91 103 FA Mahnaz Kayyal 1MSc of Medical-Surgical Nursing, School of Nursing and Midwifery, Birjand University of Medical Sciences, Birjand, Iran Mahnaz Kayyal 1MSc of Medical-Surgical Nursing, School of Nursing and Midwifery, Birjand University of Medical Sciences, Birjand, Iran Mahnoush Khalilian 2Medical student, Üsküdar Universitesi, Istanbul, Türkiye Mahnoush Khalilian 2Medical student, Üsküdar Universitesi, Istanbul, Türkiye Leyla Nazarpoor Akbari 3Master of Medical Biochemistry, Department of Comparative Bioscience, Faculty of Veterinary Medicine, University of Tehran, Iran Leyla Nazarpoor Akbari 3Master of Medical Biochemistry, Department of Comparative Bioscience, Faculty of Veterinary Medicine, University of Tehran, Iran Mohammadmehdi Salehi 4Bachelor of Anesthesiology, Aja University of Medical Sciences, Tehran, Iran Mohammadmehdi Salehi 4Bachelor of Anesthesiology, Aja University of Medical Sciences, Tehran, Iran Ali Shahbazi 5B.Sc. in Public Health, Bagherololoom Sepidan Health Higher Education Center, Shiraz University of Medical Science, Shiraz, Iran Ali Shahbazi 5B.Sc. in Public Health, Bagherololoom Sepidan Health Higher Education Center, Shiraz University of Medical Science, Shiraz, Iran Kamyar Shafiei 6Master of Epidemiology, Yazd Shahid Sadoughi University of Medical Sciences, Yazd, Iran Kamyar Shafiei 6Master of Epidemiology, Yazd Shahid Sadoughi University of Medical Sciences, Yazd, Iran 2026 08 18 Wearable biosensors and artificial intelligence (AI) are transforming modern healthcare by enabling continuous, real-time, and personalized health monitoring. Wearable biosensors can continuously measure physiological and biochemical parameters such as heart rate, body temperature, blood oxygen saturation, glucose levels, and physical activity, while AI techniques process these large and complex datasets to generate meaningful clinical insights. This review examines recent developments in wearable biosensor technologies, AI-based health data analysis, and their integration for personalized healthcare. It discusses the classification of wearable biosensors, the application of machine learning and deep learning algorithms, and the expanding clinical use of AI-enabled wearable devices in cardiovascular care, chronic disease management, remote patient monitoring, and preventive medicine. The review also highlights major challenges related to sensor accuracy, interoperability, ethical concerns, data privacy, cybersecurity, and regulatory issues that may influence the successful implementation of these technologies. Furthermore, future trends, including intelligent health ecosystems, multimodal sensing platforms, digital twins, and precision medicine, are explored. Overall, the integration of wearable biosensors and artificial intelligence has the potential to improve diagnostic accuracy, support early disease detection, enhance patient engagement, optimize clinical decision-making, and facilitate the transition toward proactive, patient-centered, and personalized healthcare systems. Wearable biosensors and artificial intelligence (AI) are transforming modern healthcare by enabling continuous, real-time, and personalized health monitoring. Wearable biosensors can continuously measure physiological and biochemical parameters such as heart rate, body temperature, blood oxygen saturation, glucose levels, and physical activity, while AI techniques process these large and complex datasets to generate meaningful clinical insights. This review examines recent developments in wearable biosensor technologies, AI-based health data analysis, and their integration for personalized healthcare. It discusses the classification of wearable biosensors, the application of machine learning and deep learning algorithms, and the expanding clinical use of AI-enabled wearable devices in cardiovascular care, chronic disease management, remote patient monitoring, and preventive medicine. The review also highlights major challenges related to sensor accuracy, interoperability, ethical concerns, data privacy, cybersecurity, and regulatory issues that may influence the successful implementation of these technologies. Furthermore, future trends, including intelligent health ecosystems, multimodal sensing platforms, digital twins, and precision medicine, are explored. Overall, the integration of wearable biosensors and artificial intelligence has the potential to improve diagnostic accuracy, support early disease detection, enhance patient engagement, optimize clinical decision-making, and facilitate the transition toward proactive, patient-centered, and personalized healthcare systems. https://mhhjr.ir/downloadfilepdf/12521